{"title":"Resistance mutations, drug binding and drug residence times","authors":"Ran Friedman","doi":"10.1016/j.sbi.2025.103158","DOIUrl":"10.1016/j.sbi.2025.103158","url":null,"abstract":"<div><div>The rapid evolution of microorganisms and cancer cells makes it difficult to treat tumours and infectious diseases, because resistance to drugs is the rule rather than the exception. Structures or models of protein–drug complexes help to understand how mutations lead to resistance and to design better drugs. However, it is difficult to reason how small changes in the structure lead to drug resistance. Thus, protein and drug dynamics need to be considered. Strategies to increase drug residence are sought after to increase the efficacy of drugs. Computational methods to calculate the effect of mutations on drug binding and residence times are being developed and improved, but are challenging. A priori prediction of a mutation's effect on drug binding is an even greater challenge. On the other hand, knowledge about protein–drug complexes has led to the development of multiple design strategies that aim to reduce mutation-driven drug resistance.</div></div>","PeriodicalId":10887,"journal":{"name":"Current opinion in structural biology","volume":"95 ","pages":"Article 103158"},"PeriodicalIF":6.1,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145085329","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Recent advances in artificial intelligence–driven biomolecular dynamics simulations based on machine learning force fields","authors":"Taoyong Cui , Yutao Zhou , Tong Wang","doi":"10.1016/j.sbi.2025.103191","DOIUrl":"10.1016/j.sbi.2025.103191","url":null,"abstract":"<div><div>Molecular dynamics simulations are crucial for investigating biomolecular mechanisms. The success of these simulations hinges on the accuracy, efficiency, and generalizability of the underlying force field. While classical molecular force fields are efficient yet approximate and quantum mechanics is accurate but computationally prohibitive for large systems, machine learning force fields (MLFFs) have emerged to bridge this gap. We review various MLFFs—from classically parametrized to end-to-end models—evaluating their performance in accuracy and efficiency. However, a significant challenge for MLFFs is generalizability as models trained on specific data often fail to extrapolate to unseen molecules or conformations. To address this, universal MLFFs, such as fragment-based methods like AI<sup>2</sup>BMD designed by Wang et al. and GEMS designed by Unke et al., are being developed. Beyond recent progress, we also discuss the inherent limitations and trade-offs of MLFFs. Looking forward, the integration of MLFFs with virtual cell models and coarse-grained representations is poised to enable whole-cell multiscale simulations.</div></div>","PeriodicalId":10887,"journal":{"name":"Current opinion in structural biology","volume":"95 ","pages":"Article 103191"},"PeriodicalIF":6.1,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145576092","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Membrane protein reconstitution : New possibilities for structural biology, biophysical methods, and antibody/drug discovery","authors":"Liguo Wang, Robert S. Prosser","doi":"10.1016/j.sbi.2025.103167","DOIUrl":"10.1016/j.sbi.2025.103167","url":null,"abstract":"","PeriodicalId":10887,"journal":{"name":"Current opinion in structural biology","volume":"95 ","pages":"Article 103167"},"PeriodicalIF":6.1,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145298979","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jean-Pierre Vilardaga , Satyaki Saha , Ji Young Lee , Lisa J. Clark , Ivet Bahar
{"title":"Allosteric modulation of Class B1 G protein-coupled receptor activation and signaling location in the cell","authors":"Jean-Pierre Vilardaga , Satyaki Saha , Ji Young Lee , Lisa J. Clark , Ivet Bahar","doi":"10.1016/j.sbi.2025.103170","DOIUrl":"10.1016/j.sbi.2025.103170","url":null,"abstract":"<div><div>It is now widely accepted that allosteric signaling is beyond signal transmission to, or conformational change triggered at, a distal point within a structure; it also affects different cellular pathways and functions depending on the specific allosteric modulators. A family of signaling molecules that has attracted wide attention in recent years is the Class B1 G protein-coupled receptors (GPCRs). In the classic view of GPCR signaling, cyclic adenosine monophosphate (cAMP) production is accepted to be uniquely associated with signaling events at the plasma membrane. However, a growing number of studies over the past decade, especially for the parathyroid hormone type 1 receptor (PTH<sub>1</sub>R), demonstrate that cAMP is also produced at the endosomes through a different pathway after receptor internalization. Recent advances in the structural and computational characterization of this family of allosteric receptors provide new insights into the mechanisms of their activation or inhibition, as well as determinants of differential allosteric signaling. We focus on PTH<sub>1</sub>R as a prototypical member of the family and present our current understanding of the role of selected ligands in acting as positive or negative allosteric modulators and eliciting signaling location biases in the cell.</div></div>","PeriodicalId":10887,"journal":{"name":"Current opinion in structural biology","volume":"95 ","pages":"Article 103170"},"PeriodicalIF":6.1,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145358157","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Vahap Gazi Fidan , Konuralp Ilim , Attila Gursoy , S. Banu Ozkan , Ozlem Keskin
{"title":"Rewiring enzyme regulation: Allosteric drugs and predictive tools","authors":"Vahap Gazi Fidan , Konuralp Ilim , Attila Gursoy , S. Banu Ozkan , Ozlem Keskin","doi":"10.1016/j.sbi.2025.103159","DOIUrl":"10.1016/j.sbi.2025.103159","url":null,"abstract":"<div><div>Allosteric modulation offers an increasingly attractive route for precise intervention in enzymatic pathways. This review outlines emerging strategies for the identification and exploitation of allosteric sites, emphasizing computational frameworks that integrate evolutionary, structural, and dynamic features with machine learning models. We discuss how perturbation-based simulations, network analyses, and deep mutational data are reshaping our understanding of allosteric regulation. In parallel, advances in experimental techniques have enabled validation of cryptic and functionally relevant pockets across diverse enzyme families. We further catalog FDA-approved allosteric modulators of enzymes, highlighting therapeutic designs that leverage distal regulation to enhance specificity and overcome resistance. Taken together, these developments reveal the growing utility of allostery in drug design and underscore its potential to expand the therapeutic target space beyond conventional binding sites.</div></div>","PeriodicalId":10887,"journal":{"name":"Current opinion in structural biology","volume":"95 ","pages":"Article 103159"},"PeriodicalIF":6.1,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145155579","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Strategies for studying discrete heterogeneity in situ using cryo-electron tomography","authors":"Alberto Bartesaghi","doi":"10.1016/j.sbi.2025.103186","DOIUrl":"10.1016/j.sbi.2025.103186","url":null,"abstract":"<div><div>Structural variability plays a crucial role in enabling biological function, as the ability of proteins to adopt multiple conformations allows them to perform diverse cellular tasks. Cryo-electron tomography combined with subtomogram averaging and classification has emerged as a powerful technique for elucidating the conformational dynamics of proteins in their near-native environment. Increased data availability has provided a driving force for improvements in image classification algorithms which have enabled conformational heterogeneity studies of proteins <em>in situ</em> at higher resolutions than previously possible. In particular, the use of 2D particle projections extracted from raw tilt-series paired with constrained classification strategies of projection sets has emerged as a promising strategy for classifying particles in 3D. Despite these efforts, further method development will be needed to extend the applicability of current strategies for 3D classification to more challenging biological targets, including low-molecular weight complexes and membrane proteins.</div></div>","PeriodicalId":10887,"journal":{"name":"Current opinion in structural biology","volume":"95 ","pages":"Article 103186"},"PeriodicalIF":6.1,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145511984","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Regulation of receptor tyrosine kinase hetero-interactions","authors":"Adam W. Smith , Francisco N. Barrera","doi":"10.1016/j.sbi.2025.103187","DOIUrl":"10.1016/j.sbi.2025.103187","url":null,"abstract":"<div><div>Receptor tyrosine kinases (RTKs) control myriads of cellular functions. RTKs are paradigmatic examples of receptors where activity is directly dependent on quaternary structure. In most cases, the monomeric RTK is inactive, and function arises only after a ligand binding event leads the RTK to bind to another copy of itself, activating trans-autophosphorylation of tyrosine residues. Such RTK homodimerization can be accompanied by the formation of homomers of higher stoichiometry. However, RTK monomers can also bind to a second type of RTK, forming heterodimers. RTK heteromerization is believed to result in different signaling than homomerization. Despite its importance, we have a poor understanding of the factors that define if an RTK will form homomers or heteromers. This short review covers recent discoveries on the heteromerization of RTK, in what is called the RTK interactome. We discuss its translational potential, and how ligands and membrane lipids affect heteromer formation.</div></div>","PeriodicalId":10887,"journal":{"name":"Current opinion in structural biology","volume":"95 ","pages":"Article 103187"},"PeriodicalIF":6.1,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145512045","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Old and new tactics of CRISPR-centric competition between bacteria and bacteriophages","authors":"Iktae Kim , Jeong-Yong Suh","doi":"10.1016/j.sbi.2025.103168","DOIUrl":"10.1016/j.sbi.2025.103168","url":null,"abstract":"<div><div>The CRISPR-Cas system provides adaptive immunity for prokaryotes against mobile genetic elements (MGEs) such as bacteriophages and plasmids. As a countermeasure, MGEs have evolved various anti-CRISPR (Acr) mechanisms that neutralize the CRISPR-mediated immunity. Canonical Acr proteins block target binding of Cas proteins in a stoichiometric or enzymatic manner. New findings reveal that Acr also disintegrates functional Cas complexes, induces promiscuous target binding, and mimics Cas proteins and crRNA with defective mutations. Here, we summarize a broad repertoire of structural and functional mechanisms underlying CRISPR-centric competition, highlighting recent discoveries of molecular machinery that modulates CRISPR function.</div></div>","PeriodicalId":10887,"journal":{"name":"Current opinion in structural biology","volume":"95 ","pages":"Article 103168"},"PeriodicalIF":6.1,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145307137","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}